(1) Field of Invention
The present invention relates to a bio-inspired system for action selection and, more particularly, to a bio-inspired system for action selection based on a model of the interactions between neuromodulators and prefrontal cortex.
(2) Description of Related Art
Neuromodulators such as dopamine (DA), serotonin (5-HT), and acetylcholine (ACh) affect both short- and long-term dynamics of neural circuits that represent reward, cost, and attention in that order (see the List of Incorporated Cited Literature References, Literature Reference No. 1). Recent experiments suggest that the reward and cost of actions are also partially represented in the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC), respectively (see Literature Reference Nos. 9 and 10).
Reinforcement learning and evolutionary algorithms have also been used to model resource allocation tasks (see Literature Reference Nos. 13 and 24) and, hence, action selection, in general. However, these models do not have a high degree of neurofidelity and, therefore, cannot make predictions of animal behavior based on lesion studies or neurotransmitter imbalances. Litt et al. (see Literature Reference No. 25) seeks to model prospect theory and decision affect theory using brain regions such as OFC, ACC, and dopaminergic and serotoninergic areas. Their model, however, does not model acetylcholinergic influences and has only been demonstrated on binary decisions. Previous models of action selection with neuromodulatory systems have not extensively considered prefrontal contributions or acetylcholinergic influences to action selection (see Literature Reference Nos. 11 and 12).
Each of the prior methods described above exhibits limitations that make them incomplete. Thus, a continuing need exists for a method that captures both short- and long-term dynamics in action selection based on a combination of neuromodulatory and prefrontal cortex area models.